1. Field
Embodiments of the invention generally relate to the management of complex networks (such as telecommunications networks, Internet Protocol (IP) networks, Internet/Industrial Internet of Things (IoT/IIoT), and cable networks), and more particularly to the identification and remediation of network anomalies in such networks.
2. Related Art
Traditionally, identifying and remediating outages and other performance anomalies in complex networks has relied on individual engineers having complete knowledge of the network and the interactions between all of the network elements that make it up. However, as network scale increases and the number of engineers increases with it, it becomes impractical for an individual engineer to diagnose a network fault that may ultimately be due to a variety of possible reasons such as misconfiguration or equipment failure across the country. Accordingly, there is a need for an expert self learning system for tracking network anomalies, analyzing multiple network log data streams and deriving recommended actions which are likely to resolve them and optimize network performance, and for applying this knowledge to new network anomalies.